Simon Fraser University Computational Vision Lab Lilong Shi, Brian Funt and Tim Lee
Studies of factors affecting skin colour Simple and linear model of skin Modelling Skin appearance under lights Applications: Estimate melanin and hemoglobin concentrations Correct imaged skin tones for lighting conditions
Tone correction Preserve melanin Skin tone correction Melanin/Hemoglobin separation
Appearance of human skin determined by Biological factors ▪ pigmentation, blood microcirculation, roughness, etc.. Viewing conditions ▪ Inducing lights Acquisition devices ▪ Cones in retina, RGB sensors of CCD digital cameras
Two-layered Skin Model [2] Epidermis Layer: melanin absorbance Dermis Layer: hemoglobin absorbance A layer has properties of an optical filter
Various skin colour <= melanin + hemoglobin Genetic: Race Temporary: ▪ Exposure to UV ▪ Hot bath Mixture varying by 2 independent factors Analyse melanin and hemoglobin factors
Estimate melanin and hemoglobin concentration Independent Component Analysis (ICA) – Statistical technique for revealing “hidden” factors – To “unmix” or “separate” signals composed of multiple sources – Independent and linear mixing – Related to Eigen-vector analysis
Original Source SignalsObserved SignalsMixing s1 s2 70% 30% v1 s × A = v 20% 80% v2 0% 100% v3
Melanin Hemoglobin Skin samples Melanin Hemoglobin
Typical skin spectrum Visible wavelength 400nm – 700nm Extract skin bases from observed spectrum by ICA ICA (left) 33 skin spectrum after normalization; (right) two independent basis spectrum – the melanin and hemoglobin, and the spectrum of chromophores other than melanin and hemoglobin pigments.
Arbitrary skin spectrum can be approximated constru are variables
Human vision ▪ 3 types of Photoreceptors L, M and S Cones Digital Cameras ▪ 3 sensors Red, Green, and Blue Reflectance spectrum recorded by 3 sensors => three values (R, G, B) for a skin colour
Possible skin colours lie within plane Given a pixel from skin, compute by projecting log(R,G,B) onto
Input Image [3] Melanin Image Hemoglobin Image
- Inverse melanin concentration - Inverse hemoglobin concentration
Skin appearance greatly affected by lights Reveal true skin colour by removing illum. Common lights blackbody radiation e.g. tungsten/halogen lamps, sunrise/sunset, etc Varying colour temperature T ▪ Redish -> white -> bluish
Colour: illumination times reflectance In log space, multiplication => addition: Illum. basis
In practice Drop hemoglobin basis ▪ Small angle between Illum and hemoglobin axes Ignore brightness Skin colour varying by T and
384 real skin reflectances times 67 real light sources => samples
Skin tone correction example ( UOPB DB [4] ) 20 Tone correction Preserve melanin 16 different illumination + camera settings
Skin tone correction example ( UOPB DB [4] )
Skin colour modelling: Melanin and Hemoglobin concentration Linear model in logarithm space Estimation by Independent Component Analysis Skin appearance + Light modelling: Estimates light source Preserves skin colour by melanin value Applied to digital images from CCD cameras
[1] Shi, L., and Funt, B., "Skin Colour Imaging That Is Insensitive to Lighting," Proc. AIC (Association Internationale de la Couleur) Conference on Colour Effects & Affects, Stockholm, June 2008 [2] Angelopoulou, E., Molana, R., and Daniilidis, K. “Multispectral skin color modeling,” In IEEE Conf. on Computer Vision and Pattern Recognition, volume 2, pages , Kauai, Hawaii, Dec [3] Shimizu, H., Uetsuki, K., Tsumura, N., and Miyake, Y. Analyzing the effect of cosmetic essence by independent component analysis for skin color images. In 3 rd Int. Conf. on Multispectral Color Science, pages 65-68, Joensuu, Finland, June [4] Martinkauppi, B. “Face color under varying illumination-analysis and applications,” Ph.D. Dissertation, University of Oulu, 2002.